OpenRaiser/Intern-Atlas huggingface dataset:
Structural and Functional Discovery in Dynamic Networks with Non-negative Matrix Factorization
Venue: arXiv cs.SI 2013
Year: 2013

Time series of graphs are increasingly prevalent in modern data and pose unique challenges to visual exploration and pattern extraction. This paper describes the development and application of matrix factorizations for exploration and time-varying community detection in time-evolving graph sequences. The matrix factorization model allows the user to home in on and display interesting, underlying structure and its evolution over time. The methods are scalable to weighted networks with a large number of time points or nodes, and can accommodate sudden changes to graph topology. Our techniques are demonstrated with several dynamic graph series from both synthetic and real world data, including citation and trade networks. These examples illustrate how users can steer the techniques and combine them with existing methods to discover and display meaningful patterns in sizable graphs over many time points.
Collaborative ontology sharing and editing
Venue: arXiv cs.AI 2013
Year: 2013

This article first lists reasons why - in the long term or when creating a new knowledge base (KB) for general knowledge sharing purposes - collaboratively building a well-organized KB does/can provide more possibilities, with on the whole no more costs, than the mainstream approach where knowledge creation and re-use involves searching, merging and creating (semi-)independent (relatively small) ontologies or semi-formal documents. The article lists elements required to achieve this and describes the main one: a KB editing protocol that keeps the KB free of automatically/manually detected inconsistencies while not forcing them to discuss or agree on terminology and beliefs nor requiring a selection committee.
Harnessing Simultaneously the Benefits of UWB and MBWA: A Practical Scenario
Venue: arXiv cs.IT 2013
Year: 2013

UWB has a very large bandwidth in a WPAN network, which is best used for HD-video applications. Meanwhile, MBWA is a WMAN option optimized for wireless-IP in a fast moving vehicle. In this paper, we propose a practical engineering scenario that harnesses simultaneously the distinctive feature of both UWB and MBWA. However, this in-proximity operation of the technologies will inevitably cause mutual interference to both systems. In light of this, as a preliminary phase to coexistence, we have derived, under various circumstances, the maximum interference power limit that needs to be respected in order to ensure an acceptable system performance as requested by the new IEEE 802.20 standard.
Joint Spatial Division and Multiplexing: Opportunistic Beamforming and User Grouping
Venue: arXiv cs.IT 2013
Year: 2013

Joint Spatial Division and Multiplexing (JSDM) is a recently proposed scheme to enable massive MIMO like gains and simplified system operations for Frequency Division Duplexing (FDD) systems. The key idea lies in partitioning the users into groups with approximately similar covariances, and use a two stage downlink beamforming: a pre-beamformer that depends on the channel covariances and minimizes interference across groups and a multiuser MIMO precoder for the effective channel after pre-beamforming, to counteract interference within a group. We first focus on the regime of a fixed number of antennas and large number of users, and show that opportunistic beamforming with user selection yields significant gain, and thus, channel correlation may yield a capacity improvement over the uncorrelated "isotropic" channel result of Sharif and Hassibi. We prove that in the presence of different correlations among groups, a block diagonalization approach for the design of pre-beamformers achieves the optimal sum-rate scaling. Next, we consider the regime of large number of antennas and users, where user selection does not provide significant gain. Here, we propose a simplified user grouping algorithm to cluster users into groups when the number of antennas becomes very large, in a realistic setting where users are randomly distributed and have different angles of arrival and angular spreads depending on the propagation environment. Our subsequent analysis leads to a probabilistic scheduling algorithm, where users within each group are preselected at random based on probabilities derived from the large system analysis, depending on the fairness criterion. This is advantageous since only the selected users are required to feedback their channel state information (CSIT).
Evaluating Different Cost-Benefit Analysis Methods for Port Security Operations
Venue: arXiv cs.CE 2013
Year: 2013

Service industries, such as ports, are attentive to their standards, a smooth service flow and economic viability. Cost benefit analysis has proven itself as a useful tool to support this type of decision making; it has been used by businesses and governmental agencies for many years. In this book chapter we demonstrate different modelling methods that are used for estimating input factors required for conducting cost benefit analysis based on a single case study. These methods are: scenario analysis, decision trees, Monte-Carlo simulation modelling and discrete event simulation modelling. Our aims are, on the one hand, to guide the analyst through the modelling processes and, on the other hand, to demonstrate what additional decision support information can be obtained from applying each of these modelling methods.
Dynamical Systems to Monitor Complex Networks in Continuous Time
Venue: arXiv cs.SI 2013
Year: 2013

In many settings it is appropriate to treat the evolution of pairwise interactions over continuous time. We show that new Katz-style centrality measures can be derived in this context via solutions to a nonautonomous ODE driven by the network dynamics. This allows us to identify and track, at any resolution, the most influential nodes in terms of broadcasting and receiving information through time dependent links. In addition to the classical notion of attenuation across edges used in the static Katz centrality measure, the ODE also allows for attenuation over time, so that real time "running measures" can be computed. With regard to computational efficiency, we explain why it is cheaper to track good receivers of information than good broadcasters. We illustrate the new measures on a large scale voice call network, where key features are discovered that are not evident from snapshots or aggregates.
Motif Detection Inspired by Immune Memory (JORS)
Venue: arXiv cs.NE 2013
Year: 2013

The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify variable length unknown motifs which repeat within time series data. The algorithm searches from a neutral perspective that is independent of the data being analysed and the underlying motifs. In this paper we test the flexibility of the motif tracking algorithm by applying it to the search for patterns in two industrial data sets. The algorithm is able to identify a population of meaningful motifs in both cases, and the value of these motifs is discussed.
Privileged Information for Data Clustering
Venue: arXiv cs.LG 2013
Year: 2013

Many machine learning algorithms assume that all input samples are independently and identically distributed from some common distribution on either the input space X, in the case of unsupervised learning, or the input and output space X x Y in the case of supervised and semi-supervised learning. In the last number of years the relaxation of this assumption has been explored and the importance of incorporation of additional information within machine learning algorithms became more apparent. Traditionally such fusion of information was the domain of semi-supervised learning. More recently the inclusion of knowledge from separate hypothetical spaces has been proposed by Vapnik as part of the supervised setting. In this work we are interested in exploring Vapnik's idea of master-class learning and the associated learning using privileged information, however within the unsupervised setting. Adoption of the advanced supervised learning paradigm for the unsupervised setting instigates investigation into the difference between privileged and technical data. By means of our proposed aRi-MAX method stability of the KMeans algorithm is improved and identification of the best clustering solution is achieved on an artificial dataset. Subsequently an information theoretic dot product based algorithm called P-Dot is proposed. This method has the ability to utilize a wide variety of clustering techniques, individually or in combination, while fusing privileged and technical data for improved clustering. Application of the P-Dot method to the task of digit recognition confirms our findings in a real-world scenario.
Ada-MAC: An Adaptive MAC Protocol for Real-time and Reliable Health Monitoring,
Venue: arXiv cs.NI 2013
Year: 2013

IEEE 802.15.4 is regarded as one of the most suitable communication protocols for cyber-physical applications of wireless sensor and actuator networks. This is because this protocol is able to achieve low-power and low-cost transmission in wireless personal area networks. But most cyber-physical systems (CPSs) require a degree of real-time and reliability from the underlying communication protocol. Some of them are stricter than the others. However, IEEE 802.15.4 protocol cannot provide reliability and real-time transmission for time-critical and delay-sensitive data in cyber-physical applications. To solve this problem, we propose a new MAC protocol, i.e. the Ada-MAC protocol, which is based on IEEE 802.15.4 beacon-enabled mode. It can support cyber-physical applications such as health monitoring, which require stringent real- time and reliability guarantees. We implement the proposed protocol on the OMNET++ platform and conduct a performance evaluation of the proposed protocol with comparison against the traditional IEEE 802.15.4 protocol. The results are presented and analyzed.
Understanding ACT-R - an Outsider's Perspective
Venue: arXiv cs.LG 2013
Year: 2013

The ACT-R theory of cognition developed by John Anderson and colleagues endeavors to explain how humans recall chunks of information and how they solve problems. ACT-R also serves as a theoretical basis for "cognitive tutors", i.e., automatic tutoring systems that help students learn mathematics, computer programming, and other subjects. The official ACT-R definition is distributed across a large body of literature spanning many articles and monographs, and hence it is difficult for an "outsider" to learn the most important aspects of the theory. This paper aims to provide a tutorial to the core components of the ACT-R theory.
ChaMAILeon: Exploring the Usability of a Privacy Preserving Email Sharing System
Venue: arXiv cs.CY 2013
Year: 2013

While passwords, by definition, are meant to be secret, recent trends have witnessed an increasing number of people sharing their email passwords with friends, colleagues, and significant others. However, leading websites like Google advise their users not to share their passwords with anyone, to avoid security and privacy breaches. To understand users' general password sharing behavior and practices, we conducted an online survey with 209 Indian participants and found that 64.35% of the participants felt a need to share their email passwords. Further, about 77% of the participants said that they would want to use a system which could provide them access control features, to maintain their privacy while sharing emails. To address the privacy concerns of users who need to share emails, we propose ChaMAILeon, a system which enables users to share their email passwords while maintaining their privacy. ChaMAILeon allows users to create multiple passwords for their email account. Each such password corresponds to a different set of access control rules, and gives a different view of the same email account. We conducted a controlled experiment with 30 participants to evaluate the usability of the system. Each participant was required to perform 5 tasks. Each task corresponded to different access control rules, which the participant was required to set, for a dummy email account. We found that, with a reasonable number of multiple attempts, all 30 participants were able to perform all 5 tasks given to them. The system usability score was found out to be 75.42. Moreover, 56.6% of the participants said that they would like to use ChaMAILeon frequently.
Survey on QoE\QoS Correlation Models For Multimedia Services
Venue: arXiv cs.MM 2013
Year: 2013

This paper presents a brief review of some existing correlation models which attempt to map Quality of Service (QoS) to Quality of Experience (QoE) for multimedia services. The term QoS refers to deterministic network behaviour, so that data can be transported with a minimum of packet loss, delay and maximum bandwidth. QoE is a subjective measure that involves human dimensions; it ties together user perception, expectations, and experience of the application and network performance. The Holy Grail of subjective measurement is to predict it from the objective measurements; in other words predict QoE from a given set of QoS parameters or vice versa. Whilst there are many quality models for multimedia, most of them are only partial solutions to predicting QoE from a given QoS. This contribution analyses a number of previous attempts and optimisation techniquesthat can reliably compute the weighting coefficients for the QoS/QoE mapping.
Hybrid Optical and Electrical Network Flows Scheduling in Cloud Data Centres
Venue: arXiv cs.NI 2013
Year: 2013

Hybrid intra-data centre networks, with optical and electrical capabilities, are attracting research interest in recent years. This is attributed to the emergence of new bandwidth greedy applications and novel computing paradigms. A key decision to make in networks of this type is the selection and placement of suitable flows for switching in circuit network. Here, we propose an efficient strategy for flow selection and placement suitable for hybrid Intra-cloud data centre networks. We further present techniques for investigating bottlenecks in a packet networks and for the selection of flows to switch in circuit network. The bottleneck technique is verified on a Software Defined Network (SDN) testbed. We also implemented the techniques presented here in a scalable simulation experiment to investigate the impact of flow selection on network performance. Results obtained from scalable simulation experiment indicate a considerable improvement on average throughput, lower configuration delay, and stability of offloaded flows
Guided Random Forest in the RRF Package
Venue: arXiv cs.LG 2013
Year: 2013

Random Forest (RF) is a powerful supervised learner and has been popularly used in many applications such as bioinformatics. In this work we propose the guided random forest (GRF) for feature selection. Similar to a feature selection method called guided regularized random forest (GRRF), GRF is built using the importance scores from an ordinary RF. However, the trees in GRRF are built sequentially, are highly correlated and do not allow for parallel computing, while the trees in GRF are built independently and can be implemented in parallel. Experiments on 10 high-dimensional gene data sets show that, with a fixed parameter value (without tuning the parameter), RF applied to features selected by GRF outperforms RF applied to all features on 9 data sets and 7 of them have significant differences at the 0.05 level. Therefore, both accuracy and interpretability are significantly improved. GRF selects more features than GRRF, however, leads to better classification accuracy. Note in this work the guided random forest is guided by the importance scores from an ordinary random forest, however, it can also be guided by other methods such as human insights (by specifying $λ_i$). GRF can be used in "RRF" v1.4 (and later versions), a package that also includes the regularized random forest methods.
One Time Pad Password Protection: Using T.E.C. Steganography and Secure Password Transmission Protocols
Venue: arXiv cs.CR 2013
Year: 2013

A while ago, I developed what I called an encryption method. The most favorable of reviews did not see a method but a collection of techniques. Be that as it may, the process used, is described in the paper, Windtalking Computers. This paper is about the steganographic method described, the cryptanalysis efforts of that method and; a real world application of that method as an answer to the increasing problem of password file hacking. The premise is that the technique is a variant of one time pad, using a novel way to produce one time pad output for digital input. There is no record in the literature of such a method being used for encryption at all. Digital encryption generally treats the letters of the plaintext as a binary number and does some mathematical computation to produce ciphertext. The idea of inserting bits with a random generated key is new. Therefore (because a uniquely random generated key is used), the encryption is cryptanalytically unbreakable and/or computationally secure and/or information theoretic. An academic version was made. Challenges for decryption have not produced to-date a decryption. Advantages and disadvantages of the method are discussed. Hackers are constantly penetrating networks and stealing password files. Which, once in possession of a password file, hackers individually or collectively with distributed processing over the Internet, decrypt the values of the hash passwords. Thereby gaining access to systems. This problem has become sufficiently significant for CAESAR (Competition for Authenticated Encryption: Security, Applicability, and Robustness) to make calls for papers for solutions. Herein is one proposed solution. While one time pad presents a problem being computationally intensive, for the relatively short length of passwords, the cost of computation may be cost effective for the security provided.
Orthogonal Range Searching for Text Indexing
Venue: arXiv cs.DS 2013
Year: 2013

Text indexing, the problem in which one desires to preprocess a (usually large) text for future (shorter) queries, has been researched ever since the suffix tree was invented in the early 70's. With textual data continuing to increase and with changes in the way it is accessed, new data structures and new algorithmic methods are continuously required. Therefore, text indexing is of utmost importance and is a very active research domain. Orthogonal range searching, classically associated with the computational geometry community, is one of the tools that has increasingly become important for various text indexing applications. Initially, in the mid 90's there were a couple of results recognizing this connection. In the last few years we have seen an increase in use of this method and are reaching a deeper understanding of the range searching uses for text indexing. In this monograph we survey some of these results.
Composition limits and separating examples for some Boolean function complexity measures
Venue: arXiv cs.CC 2013
Year: 2013

Block sensitivity ($bs(f)$), certificate complexity ($C(f)$) and fractional certificate complexity ($C^*(f)$) are three fundamental combinatorial measures of complexity of a boolean function $f$. It has long been known that $bs(f) \leq C^{\ast}(f) \leq C(f) =O(bs(f)^2)$. We provide an infinite family of examples for which $C(f)$ grows quadratically in $C^{\ast}(f)$ (and also $bs(f)$) giving optimal separations between these measures. Previously the biggest separation known was $C(f)=C^{\ast}(f)^{\log_{4.5}5}$. We also give a family of examples for which $C^{\ast}(f)=Ω(bs(f)^{3/2})$. These examples are obtained by composing boolean functions in various ways. Here the composition $f \circ g$ of $f$ with $g$ is obtained by substituting for each variable of $f$ a copy of $g$ on disjoint sets of variables. To construct and analyse these examples we systematically investigate the behaviour under function composition of these measures and also the sensitivity measure $s(f)$. The measures $s(f)$, $C(f)$ and $C^{\ast}(f)$ behave nicely under composition: they are submultiplicative (where measure $m$ is submultiplicative if $m(f \circ g) \leq m(f)m(g)$) with equality holding under some fairly general conditions. The measure $bs(f)$ is qualitatively different: it is not submultiplicative. This qualitative difference was not noticed in the previous literature and we correct some errors that appeared in previous papers. We define the composition limit of a measure $m$ at function $f$, $m^{\lim}(f)$ to be the limit as $k$ grows of $m(f^{(k)})^{1/k}$, where $f^{(k)}$ is the iterated composition of $f$ with itself $k$-times. For any function $f$ we show that $bs^{\lim}(f) = (C^*)^{\lim}(f)$ and characterize $s^{\lim}(f), (C^*)^{\lim}(f)$, and $C^{\lim}(f)$ in terms of the largest eigenvalue of a certain set of $2\times 2$ matrices associated with $f$.
Narrative based Postdictive Reasoning for Cognitive Robotics
Venue: arXiv cs.AI 2013
Year: 2013

Making sense of incomplete and conflicting narrative knowledge in the presence of abnormalities, unobservable processes, and other real world considerations is a challenge and crucial requirement for cognitive robotics systems. An added challenge, even when suitably specialised action languages and reasoning systems exist, is practical integration and application within large-scale robot control frameworks. In the backdrop of an autonomous wheelchair robot control task, we report on application-driven work to realise postdiction triggered abnormality detection and re-planning for real-time robot control: (a) Narrative-based knowledge about the environment is obtained via a larger smart environment framework; and (b) abnormalities are postdicted from stable-models of an answer-set program corresponding to the robot's epistemic model. The overall reasoning is performed in the context of an approximate epistemic action theory based planner implemented via a translation to answer-set programming.
Hennessy-Milner Logic with Greatest Fixed Points as a Complete Behavioural Specification Theory
Venue: arXiv cs.LO 2013
Year: 2013

There are two fundamentally different approaches to specifying and verifying properties of systems. The logical approach makes use of specifications given as formulae of temporal or modal logics and relies on efficient model checking algorithms; the behavioural approach exploits various equivalence or refinement checking methods, provided the specifications are given in the same formalism as implementations. In this paper we provide translations between the logical formalism of Hennessy-Milner logic with greatest fixed points and the behavioural formalism of disjunctive modal transition systems. We also introduce a new operation of quotient for the above equivalent formalisms, which is adjoint to structural composition and allows synthesis of missing specifications from partial implementations. This is a substantial generalisation of the quotient for deterministic modal transition systems defined in earlier papers.
Detecting Missing Method Calls as Violations of the Majority Rule
Venue: arXiv cs.SE 2013
Year: 2013

When using object-oriented frameworks it is easy to overlook certain important method calls that are required at particular places in code. In this paper, we provide a comprehensive set of empirical facts on this problem, starting from traces of missing method calls in a bug repository. We propose a new system that searches for missing method calls in software based on the other method calls that are observable. Our key insight is that the voting theory concept of majority rule holds for method calls: a call is likely to be missing if there is a majority of similar pieces of code where this call is present. The evaluation shows that the system predictions go further missing method calls and often reveal different kinds of code smells (e.g. violations of API best practices).